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        <a href="windenergytk-module.html">Package&nbsp;windenergytk</a> ::
        Module&nbsp;analysis
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<!-- ==================== MODULE DESCRIPTION ==================== -->
<h1 class="epydoc">Module analysis</h1><p class="nomargin-top"><span class="codelink"><a href="windenergytk.analysis-pysrc.html">source&nbsp;code</a></span></p>
<!-- ==================== FUNCTIONS ==================== -->
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          <td><span class="summary-sig"><a href="windenergytk.analysis-module.html#get_statistics" class="summary-sig-name">get_statistics</a>(<span class="summary-sig-arg">timeseries</span>,
        <span class="summary-sig-arg">output</span>=<span class="summary-sig-default"><code class="variable-quote">'</code><code class="variable-string">dictionary</code><code class="variable-quote">'</code></span>)</span><br />
      Collects statistics from a timeseries object.</td>
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            <span class="codelink"><a href="windenergytk.analysis-pysrc.html#get_statistics">source&nbsp;code</a></span>
            
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          <td><span class="summary-sig"><a href="windenergytk.analysis-module.html#get_histogram_data" class="summary-sig-name">get_histogram_data</a>(<span class="summary-sig-arg">timeseries</span>,
        <span class="summary-sig-arg">bins</span>=<span class="summary-sig-default">10</span>,
        <span class="summary-sig-arg">normalized</span>=<span class="summary-sig-default">True</span>)</span><br />
      Returns histogram data of timeseries object Input: timeseries obj.</td>
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            <span class="codelink"><a href="windenergytk.analysis-pysrc.html#get_histogram_data">source&nbsp;code</a></span>
            
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          <td><span class="summary-sig"><a href="windenergytk.analysis-module.html#get_weibull_params" class="summary-sig-name">get_weibull_params</a>(<span class="summary-sig-arg">mean</span>,
        <span class="summary-sig-arg">stdev</span>)</span><br />
      Returns Weibull parameters c and k.</td>
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            <span class="codelink"><a href="windenergytk.analysis-pysrc.html#get_weibull_params">source&nbsp;code</a></span>
            
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          <td><span class="summary-sig"><a href="windenergytk.analysis-module.html#crosscorrelate" class="summary-sig-name">crosscorrelate</a>(<span class="summary-sig-arg">timeseries1</span>,
        <span class="summary-sig-arg">timeseries2</span>,
        <span class="summary-sig-arg">max_lag_increment</span>=<span class="summary-sig-default">False</span>)</span><br />
      Returns crosscorrelation values at lag increments.</td>
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            <span class="codelink"><a href="windenergytk.analysis-pysrc.html#crosscorrelate">source&nbsp;code</a></span>
            
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          <td><span class="summary-sig"><a href="windenergytk.analysis-module.html#autocorrelate" class="summary-sig-name">autocorrelate</a>(<span class="summary-sig-arg">timeseries</span>,
        <span class="summary-sig-arg">max_lag_increment</span>=<span class="summary-sig-default">False</span>)</span><br />
      Returns autocorrelation values at lag increments.</td>
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            <span class="codelink"><a href="windenergytk.analysis-pysrc.html#autocorrelate">source&nbsp;code</a></span>
            
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          <td><span class="summary-sig"><a href="windenergytk.analysis-module.html#block_average" class="summary-sig-name">block_average</a>(<span class="summary-sig-arg">timeseries</span>,
        <span class="summary-sig-arg">new_freq</span>=<span class="summary-sig-default"><code class="variable-quote">'</code><code class="variable-string"></code><code class="variable-quote">'</code></span>)</span><br />
      Reduce size of timeseries by taking averages of larger block size.</td>
          <td align="right" valign="top">
            <span class="codelink"><a href="windenergytk.analysis-pysrc.html#block_average">source&nbsp;code</a></span>
            
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          <td><span class="summary-sig"><a name="power_spectral_density"></a><span class="summary-sig-name">power_spectral_density</span>(<span class="summary-sig-arg">data_array</span>,
        <span class="summary-sig-arg">frequency</span>,
        <span class="summary-sig-arg">window_method</span>=<span class="summary-sig-default">False</span>)</span></td>
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            <span class="codelink"><a href="windenergytk.analysis-pysrc.html#power_spectral_density">source&nbsp;code</a></span>
            
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        <a name="__package__"></a><span class="summary-name">__package__</span> = <code title="'windenergytk'"><code class="variable-quote">'</code><code class="variable-string">windenergytk</code><code class="variable-quote">'</code></code>
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<a name="get_statistics"></a>
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  <h3 class="epydoc"><span class="sig"><span class="sig-name">get_statistics</span>(<span class="sig-arg">timeseries</span>,
        <span class="sig-arg">output</span>=<span class="sig-default"><code class="variable-quote">'</code><code class="variable-string">dictionary</code><code class="variable-quote">'</code></span>)</span>
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    ><span class="codelink"><a href="windenergytk.analysis-pysrc.html#get_statistics">source&nbsp;code</a></span>&nbsp;
    </td>
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  <p>Collects statistics from a timeseries object.</p>
  <p>Input: A timeseries object, output format ('dictionary' or 'list') 
  Output: Dictionary or array of mean, stdev, max, min, size</p>
  <dl class="fields">
  </dl>
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  <h3 class="epydoc"><span class="sig"><span class="sig-name">get_histogram_data</span>(<span class="sig-arg">timeseries</span>,
        <span class="sig-arg">bins</span>=<span class="sig-default">10</span>,
        <span class="sig-arg">normalized</span>=<span class="sig-default">True</span>)</span>
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    ><span class="codelink"><a href="windenergytk.analysis-pysrc.html#get_histogram_data">source&nbsp;code</a></span>&nbsp;
    </td>
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  <p>Returns histogram data of timeseries object Input: timeseries obj. 
  Optional: No. of bins (default is 10), normalized (boolean) Output: Tuple
  (bins, histogram)</p>
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  </dl>
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  <h3 class="epydoc"><span class="sig"><span class="sig-name">get_weibull_params</span>(<span class="sig-arg">mean</span>,
        <span class="sig-arg">stdev</span>)</span>
  </h3>
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    ><span class="codelink"><a href="windenergytk.analysis-pysrc.html#get_weibull_params">source&nbsp;code</a></span>&nbsp;
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  <p>Returns Weibull parameters c and k. Input: mean, stdev Output: Weibull
  scale: c, shape: k Citation: Manwell 2000, chapter 2</p>
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  </dl>
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<a name="crosscorrelate"></a>
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  <h3 class="epydoc"><span class="sig"><span class="sig-name">crosscorrelate</span>(<span class="sig-arg">timeseries1</span>,
        <span class="sig-arg">timeseries2</span>,
        <span class="sig-arg">max_lag_increment</span>=<span class="sig-default">False</span>)</span>
  </h3>
  </td><td align="right" valign="top"
    ><span class="codelink"><a href="windenergytk.analysis-pysrc.html#crosscorrelate">source&nbsp;code</a></span>&nbsp;
    </td>
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  <p>Returns crosscorrelation values at lag increments. Input: timeseries1,
  timeseries2 Optional: max_lag_increment (int) Output: array of lags, 
  array of correlation values</p>
  <dl class="fields">
  </dl>
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<a name="autocorrelate"></a>
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  <h3 class="epydoc"><span class="sig"><span class="sig-name">autocorrelate</span>(<span class="sig-arg">timeseries</span>,
        <span class="sig-arg">max_lag_increment</span>=<span class="sig-default">False</span>)</span>
  </h3>
  </td><td align="right" valign="top"
    ><span class="codelink"><a href="windenergytk.analysis-pysrc.html#autocorrelate">source&nbsp;code</a></span>&nbsp;
    </td>
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  <p>Returns autocorrelation values at lag increments. Input: a single 
  timeseries object optional: max_lag_increment Output: Array of lags, 
  Array of normalized autocorrelation values.</p>
  <dl class="fields">
  </dl>
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  <h3 class="epydoc"><span class="sig"><span class="sig-name">block_average</span>(<span class="sig-arg">timeseries</span>,
        <span class="sig-arg">new_freq</span>=<span class="sig-default"><code class="variable-quote">'</code><code class="variable-string"></code><code class="variable-quote">'</code></span>)</span>
  </h3>
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    ><span class="codelink"><a href="windenergytk.analysis-pysrc.html#block_average">source&nbsp;code</a></span>&nbsp;
    </td>
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  <p>Reduce size of timeseries by taking averages of larger block size. 
  Input: timeseries, new_freq (str) See scikits.timeseries doc Output: 
  block averaged timeseries obj. in new frequency</p>
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